手法を比較

	多層確率ブロックモデル	多層コミュニティ検出
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	2015-2017	2010–2014
提唱者	Peixoto, T. P.; De Bacco, C. and colleagues	Mucha, P. J. et al.; Kivela, M. et al.
種類	Generative probabilistic model	Community detection algorithm for multilayer networks
原典	Peixoto, T. P. (2015). Inferring the mesoscale structure of layered, edge-valued, and time-varying networks. Physical Review E, 92(4), 042807.	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.
別名	ML-SBM, multilayer SBM, multi-layer stochastic block model, multiplex stochastic block model	multilayer clustering, multiplex community detection, cross-layer community detection, MCD
関連	4	5
概要	The Multilayer Stochastic Block Model (ML-SBM) is a generative probabilistic framework that extends the classical stochastic block model to networks with multiple relation types or layers. It simultaneously infers community structure and block-to-block connection probabilities across all layers, capturing how communities cohere differently depending on context or relationship type.	Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss.